Many variants to AMP have been proposed to address the divergence issue and achieve better robustness to blacka generic \(\mathbf { A }\) , such as the damped AMP [1]}, swept AMP [2]}, blackgeneralized approximate message passing algorithm (GAMP) with adaptive damping [3]}, vector AMP [4]}, orthogonal AMP [5]}, blackmemory AMP [6]}, convolutional AMP [7]} and more. In [8]}, blackby incorporating damped Gaussian generalized AMP (GGAMP) to the EM-based SBL method, a GGAMP-SBL algorithm was proposed. Although the robustness of the approach is significantly improved, it comes at the cost of slowing the convergence. blackIn addition, the algorithm still exhibits significant performance gap from the support-oracle bound when the measurement matrix has relatively high correlation, large condition number or non-zero mean.
